Information theory provides the fundamental framework for understanding and designing data compression algorithms. At its core lies the concept of entropy, a quantitative measure that reflects the ...

Coding, information theory and compression constitute the backbone of modern digital communications and data storage. Grounded in Shannon’s seminal work, information theory quantifies the ...

Green, Jerry R., and Jean-Jacques Laffont. "Incentive Theory with Data Compression." In Uncertainty, Information and Communication: Essays in Honor of Kenneth J ...

New research challenges a popular conception of how machine learning algorithms 'think' about certain tasks. New research challenges a popular conception of how machine learning algorithms "think" ...

The act of "zipping" a computer file or directory into a smaller format has become routine, even though the practice may seem like some dark art of wizardry. Compressing a stack of blankets for ...

Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks (DNNs) have become one of the most popular research ...

This course gives students analytical tools to quantify information, perform inference, and study the relationship of information and learning. The course covers information measures, the source and ...

In a video from the early 1950s, Bell Labs scientist Claude Shannon demonstrates one of his new inventions: a toy mouse named Theseus that looks like it could be a wind-up. The gaunt Shannon, looking ...

Efficient data compression and transmission are crucial in space missions due to restricted resources, such as bandwidth and storage capacity. This requires efficient data-compression methods that ...

A few weeks ago, I was invited to visit the New York City office of XLABS, a group that claims to have achieved 99% compression for videos being streamed over the Internet. If the claim is valid, its ...